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AbstractHigh‐performance dye‐sensitized solar cell (DSSC) devices rely on photoanodes that possess excellent light‐harvesting capabilities and high surface areas for sufficient dye adsorption. In this work, morphologically controlled SnO2 microstructures were synthesized and used as an efficient light‐backscattering layer on top of a nanocrystalline TiO2 layer to prepare a double‐layered photoanode. By optimizing the thickness of both the TiO2 bottom layer and the SnO2 top layer, a high power conversion efficiency (PCE) of 7.8 % was achieved, an enhancement of approximately 38 % in the efficiency compared with that of a nanocrystalline TiO2‐only photoanode (5.6 %). We attribute this efficiency improvement to the superior light‐backscattering capability of the SnO2 microstructures.

SUMMARY In the study, a 2D, non-isothermal, heterogeneous model of a triglyceride hydrocracking reactor is investigated. The internal heat and mass transfer within the phases in the reactor were considered using the film theory. The conservation equations for energy and mass were solved simultaneously using appropriate numerical techniques whose reliability was assessed by comparison of the results with previously reported experimental data. The modelling was performed with consideration of two proposed hydrocracking kinetic models. The model predictions showed reasonable correlation with published experimental data and conversion rates. The calculations indicated that at feed temperature of 380 °C, liquid hourly space velocity of 8 h−1 and hydrogen : feed ratio of 1500:1, the total triglyceride conversion was 82.54% for four major classes of hydrocarbons (light, middle, heavy and oligomerised). In addition, the concentration distribution and temperature profile along the reactor were investigated. The product concentrations along the reactor show that higher rates of production at the beginning of the reactor were achieved because of high concentration of triglyceride due to the exothermic hydrocracking reactions and counter-current flow modes of triglyceride and hydrogen; a jump of 90 °C was shown at the beginning of the reactor temperature profile. Copyright © 2014 John Wiley & Sons, Ltd.

This study investigates the effect of engine temperature during cold start and hot start engine operation on particulate matter emissions and engine performance parameters. In addition to a fundamental study on cold start operation and the effect of lubricating oil during combustion, this research introduces important knowledge about regulated particulate number emissions and particulate size distribution during cold start, which is an emerging area in the literature. A further aspect of this work is to introduce waste lubricating oil as a fuel. By using diesel and two blends of diesel with 1 and 5% waste lubricating oil in a 6-cylinder turbocharged engine on a cold start custom test, this investigation studied particle number (PN), friction losses and combustion instability with diesel and waste lubricating oil fuel blends. In order to understand and explain the results the following were also studied: particle size distribution and median diameter, engine oil, coolant and exhaust gas temperatures, start of injection, friction mean effective pressure (FMEP), mechanical efficiency, coefficient of variation (CoV) of engine speed, CoV of indicated mean effective pressure (IMEP) and maximum rate of pressure rise were also studied. The results showed that during cold start the increase in engine temperature was associated with an increase in PN and size of particles, and a decrease in FMEP and maximum rate of pressure rise. Compared to a warmed up engine, during cold start, PN, start of injection and mechanical efficiency were lower; while FMEP, CoV of IMEP and maximum rate of pressure rise were higher. Adding 5% waste lubricating oil to the fuel was associated with a decrease in PN (during cold start), decreased particle size, maximum rate of pressure rise and CoV of IMEP and was associated with an increase in PN and nucleation mode particles (during hot start) and FMEP

Advanced metering technologies coupled with informatics creates an opportunity to form digital multi-utility service providers. These providers will be able to concurrently collect a customers’ medium-high resolution water, electricity and gas demand data and provide user-friendly platforms to feed this information back to customers and supply/distribution utility organisations. Providers that can install low-cost integrative systems will reap the benefits of derived operational synergies and access to mass markets not bounded by historical city, state or country limits. This paper provides a vision of the required transformative process and features of an integrated multi-utility service provider covering the system architecture, opportunities and benefits, impediments and strategies, and business opportunities. The heart of the paper is focused on demonstrating data modelling processes and informatics opportunities for contemporaneously collected demand data, through illustrative examples and four informative water-energy nexus case studies. Finally, the paper provides an overview of the transformative R&D priorities to realise the vision.

A solid oxide fuel cell (SOFC) system consists of a fuel cell stack with its auxiliary components. Modelling an entire SOFC system can be simplified by employing standard process flowsheeting software. However, no in-built SOFC module exists within any of the commercial flowsheet simulators. In Amiri et al. (Comput. Chem. Eng., 2015, 78:10-23), a rigorous SOFC module was developed to fill this gap. That work outlined a multi-scale approach to SOFC modelling and presented analyses at compartment, channel and cell scales. The current work extends the approach to stack and system scales. Two case studies were conducted on a simulated multilayer, planar SOFC stack with its balance of plant (BoP) components. Firstly, the effect of flow maldistribution in the stack manifold on the SOFC's internal variables was examined. Secondly, the interaction between the stack and the BoP was investigated through the effect of recycling depleted fuel. The results showed that anode gas recycling could be used for managing the gradients within the stack, while also improving fuel utilisation and water management.

Hydrothermal liquefaction (HTL) is a promising route for producing renewable fuels and chemicals from algal biomass. However, the protein fraction of the alga gives rise to nitrogen compounds in the oil fraction, which may render the oil unattractive for use in conventional refining processes. We report a two-stage HTL approach with the primary aim of reducing the nitrogen concentration in the bio-crude oil. A mild (b200 °C) pre-treatment step (Stage I) is performed before more severe (250–350 °C) HTL conditions (Stage II) are applied to the microalga Chlorella for the production of bio-crude in a batch reactor. The pre-treatment resulted in up to 50 wt.% of the input nitrogen crossing into the Stage I aqueous phase and, following Stage II processing, reductions in the bio-crude nitrogen contents of up to 55%, relative to the direct HTL of untreated Chlorella were observed. However, since considerable amounts of the starting material were lost in Stage I, overall lower quantities of bio-crude were isolated after Stage II processing, as compared to single-stage processing. Nitrogen extraction during Stage I is enhanced by the addition of acids (1 N sulphuric or formic acid) but the process remains unselective. Overall, it is concluded that the two-stage approach to reducing the nitrogen content of bio-crudes from a protein-rich alga requires careful evaluation of the trade-off between the desired bio-crude properties and the yield obtained.

NarrowBand-Internet of Things (NB-IoT) est une nouvelle technologie d'accès radio 3GPP conçue pour fournir une meilleure couverture pour un grand nombre d'appareils à faible débit et à faible coût dans des applications tolérantes aux retards avec une faible consommation d'énergie. Pour fournir des connexions fiables avec une couverture étendue, un schéma de transmission de répétition est introduit à NB-IoT pendant la procédure de canal d'accès aléatoire (RACH) et la procédure de transmission de données. Pour éviter la difficulté de remplacer la batterie pour les appareils IoT, la récupération d'énergie est considérée comme une solution prometteuse pour soutenir la durabilité énergétique dans le réseau NB-IoT. Dans ce travail, nous analysons la probabilité de succès de RACH dans un réseau NB-IoT auto-alimenté en tenant compte des transmissions et des collisions répétées du préambule, où chaque appareil IoT avec des données est actif lorsque l'énergie de sa batterie est suffisante pour prendre en charge la transmission. Nous modélisons la dynamique temporelle du niveau d'énergie en tant que processus naissance-mort, dérivons la disponibilité énergétique de chaque dispositif IoT et examinons sa dépendance à la capacité de stockage d'énergie et à la valeur de répétition. Nous montrons que dans certains scénarios, la disponibilité énergétique reste inchangée malgré le caractère aléatoire de la collecte d'énergie. Nous dérivons également l'expression exacte de la probabilité de succès RACH d'un dispositif IoT choisi au hasard sous la disponibilité d'énergie dérivée, qui est validée sous différentes valeurs de répétition via des simulations. Nous montrons que le schéma de répétition peut améliorer efficacement la probabilité de succès de RACH dans un scénario de trafic léger, mais n'améliore que légèrement cette performance avec une utilisation très inefficace des ressources du canal dans un scénario de trafic lourd. NarrowBand-Internet of Things (NB-IoT) es una nueva tecnología de acceso por radio 3GPP diseñada para proporcionar una mejor cobertura para un gran número de dispositivos de bajo rendimiento y bajo coste en aplicaciones tolerantes a retrasos con bajo consumo de energía. Para proporcionar conexiones confiables con cobertura extendida, se introduce un esquema de transmisión de repetición en NB-IoT durante el procedimiento de canal de acceso aleatorio (RACH) y el procedimiento de transmisión de datos. Para evitar la dificultad de reemplazar la batería para dispositivos IoT, la recolección de energía se considera una solución prometedora para apoyar la sostenibilidad energética en la red NB-IoT. En este trabajo, analizamos la probabilidad de éxito de RACH en una red NB-IoT autoalimentada teniendo en cuenta las repetidas transmisiones y colisiones de preámbulos, donde cada dispositivo IoT con datos está activo cuando su energía de batería es suficiente para soportar la transmisión. Modelamos la dinámica temporal del nivel de energía como un proceso de nacimiento-muerte, derivamos la disponibilidad de energía de cada dispositivo IoT y examinamos su dependencia de la capacidad de almacenamiento de energía y el valor de repetición. Mostramos que en ciertos escenarios, la disponibilidad de energía se mantiene sin cambios a pesar de la aleatoriedad en la recolección de energía. También derivamos la expresión exacta para la probabilidad de éxito de RACH de un dispositivo IoT elegido al azar bajo la disponibilidad de energía derivada, que se valida bajo diferentes valores de repetición a través de simulaciones. Mostramos que el esquema de repetición puede mejorar de manera eficiente la probabilidad de éxito de RACH en un escenario de tráfico ligero, pero solo mejora ligeramente ese rendimiento con una utilización muy ineficiente de los recursos del canal en un escenario de tráfico pesado. NarrowBand-Internet of Things (NB-IoT) is a new 3GPP radio access technology designed to provide better coverage for a massive number of low-throughput low-cost devices in delay-tolerant applications with low power consumption. To provide reliable connections with extended coverage, a repetition transmission scheme is introduced to NB-IoT during both Random Access CHannel (RACH) procedure and data transmission procedure. To avoid the difficulty in replacing the battery for IoT devices, the energy harvesting is considered as a promising solution to support energy sustainability in the NB-IoT network. In this work, we analyze RACH success probability in a self-powered NB-IoT network taking into account the repeated preamble transmissions and collisions, where each IoT device with data is active when its battery energy is sufficient to support the transmission. We model the temporal dynamics of the energy level as a birth-death process, derive the energy availability of each IoT device, and examine its dependence on the energy storage capacity and the repetition value. We show that in certain scenarios, the energy availability remains unchanged despite randomness in the energy harvesting. We also derive the exact expression for the RACH success probability of a randomly chosen IoT device under the derived energy availability, which is validated under different repetition values via simulations. We show that the repetition scheme can efficiently improve the RACH success probability in a light traffic scenario, but only slightly improves that performance with very inefficient channel resource utilization in a heavy traffic scenario. NarrowBand - Internet of Things (NB - IoT) هي تقنية وصول لاسلكي جديدة 3GPP مصممة لتوفير تغطية أفضل لعدد كبير من الأجهزة منخفضة التكلفة منخفضة الإنتاجية في التطبيقات التي تتسامح مع التأخير مع انخفاض استهلاك الطاقة. لتوفير اتصالات موثوقة مع تغطية موسعة، يتم تقديم مخطط إرسال التكرار إلى NB - IoT خلال كل من إجراء قناة الوصول العشوائي (RACH) وإجراء نقل البيانات. لتجنب صعوبة استبدال البطارية لأجهزة إنترنت الأشياء، يعتبر حصاد الطاقة حلاً واعدًا لدعم استدامة الطاقة في شبكة إنترنت الأشياء. في هذا العمل، نقوم بتحليل احتمالية نجاح RACH في شبكة إنترنت الأشياء NB - IoT ذاتية التشغيل مع الأخذ في الاعتبار عمليات الإرسال والتصادم التمهيدية المتكررة، حيث يكون كل جهاز إنترنت الأشياء مع البيانات نشطًا عندما تكون طاقة البطارية كافية لدعم الإرسال. نقوم بنمذجة الديناميكيات الزمنية لمستوى الطاقة كعملية وفاة عند الولادة، ونستمد توافر الطاقة لكل جهاز إنترنت الأشياء، ونفحص اعتماده على سعة تخزين الطاقة وقيمة التكرار. نظهر أنه في بعض السيناريوهات، يظل توافر الطاقة دون تغيير على الرغم من العشوائية في حصاد الطاقة. نستمد أيضًا التعبير الدقيق لاحتمال نجاح راش لجهاز إنترنت الأشياء الذي تم اختياره عشوائيًا في ظل توفر الطاقة المشتقة، والذي يتم التحقق من صحته بموجب قيم تكرار مختلفة عبر عمليات المحاكاة. نظهر أن مخطط التكرار يمكن أن يحسن بكفاءة احتمال نجاح راش في سيناريو حركة المرور الخفيفة، ولكنه يحسن هذا الأداء بشكل طفيف فقط مع استخدام موارد القناة بشكل غير فعال للغاية في سيناريو حركة المرور الكثيفة.